oazeta: One-Altered Zeta Distribution

View source: R/family.vd1.R

oazetaR Documentation

One-Altered Zeta Distribution

Description

Fits a one-altered zeta distribution based on a conditional model involving a Bernoulli distribution and a 1-truncated zeta distribution.

Usage

oazeta(lpobs1 = "logitlink", lshape = "loglink",
       type.fitted = c("mean", "shape", "pobs1", "onempobs1"),
       gshape = exp((-4:3)/4), ishape = NULL, ipobs1 = NULL, zero = NULL)

Arguments

lpobs1

Link function for the parameter pobs1 or phi, called pobs1 or phi here. See Links for more choices.

lshape

See zeta for details.

type.fitted

See CommonVGAMffArguments and fittedvlm for information.

gshape, ishape, ipobs1, zero

See CommonVGAMffArguments for information.

Details

The response Y is one with probability pobs1, or Y has a 1-truncated zeta distribution with probability 1-pobs1. Thus 0 < pobs1 < 1, which is modelled as a function of the covariates. The one-altered zeta distribution differs from the one-inflated zeta distribution in that the former has ones coming from one source, whereas the latter has ones coming from the zeta distribution too. The one-inflated zeta distribution is implemented in the VGAM package. Some people call the one-altered zeta a hurdle model.

The input can be a matrix (multiple responses). By default, the two linear/additive predictors of oazeta are (logit(phi), log(shape))^T.

Value

An object of class "vglmff" (see vglmff-class). The object is used by modelling functions such as vglm, and vgam.

The fitted.values slot of the fitted object, which should be extracted by the generic function fitted, returns the mean mu (default) which is given by

mu = phi + (1- phi) A

where A is the mean of the one-truncated zeta distribution. If type.fitted = "pobs1" then pobs1 is returned.

Note

This family function effectively combines binomialff and otzeta into one family function.

Author(s)

T. W. Yee

See Also

Oazeta, zetaff, oizeta, otzeta, CommonVGAMffArguments, simulate.vlm.

Examples

## Not run: odata <- data.frame(x2 = runif(nn <- 1000))
odata <- transform(odata, pobs1 = logitlink(-1 + 2*x2, inverse = TRUE),
                          shape =  loglink( 1 + 1*x2, inverse = TRUE))
odata <- transform(odata, y1 = roazeta(nn, shape = shape, pobs1 = pobs1),
                          y2 = roazeta(nn, shape = shape, pobs1 = pobs1))
with(odata, table(y1))

ofit <- vglm(cbind(y1, y2) ~ x2, oazeta, data = odata, trace = TRUE)
coef(ofit, matrix = TRUE)
head(fitted(ofit))
head(predict(ofit))
summary(ofit)

## End(Not run)

VGAMdata documentation built on March 18, 2022, 8:03 p.m.